AI-Driven Freezing of Gait (FOG) detection in Parkinson's disease using machine learning and sensor data analysis.
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Updated
May 18, 2024 - Jupyter Notebook
AI-Driven Freezing of Gait (FOG) detection in Parkinson's disease using machine learning and sensor data analysis.
ROI-based deep learning for maritime fog detection (J-KICS 2025) — horizon-referenced regions estimate visibility-based risk from coastal CCTV.
Personalized FOG (Freezing of Gait) Detection System for Parkinson's Disease using Multimodal Biosignals (sEMG, EEG, IMU) and Hybrid Deep Learning.
A deep learning-based vehicle detection system for foggy and low-visibility environments using YOLO and image enhancement techniques. Designed for intelligent transportation systems, autonomous driving, and traffic monitoring.
An IoT-integrated hybrid deep learning system that detects vehicles in foggy environments, estimates fog density, and recommends safe driving speeds using YOLOv8, Faster R-CNN, and ThingSpeak.
Object detection in foggy road scenes using pretrained Faster R-CNN (ResNet50-FPN) in PyTorch, analyzing model robustness under low-visibility conditions.
YOLOv8 |Flask + Vue + MySQL
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